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pgvector vs Pinecone
Comparing two vector database platforms on pricing, features, free tier, and trade-offs.
Quick summary
pgvector — Vector similarity search for Postgres. pgvector is an open-source Postgres extension that adds vector similarity search to any Postgres database. Runs anywhere Postgres runs (Supabase, Neon, RDS).
Pinecone — The vector database for AI applications. Pinecone is a managed vector database purpose-built for production AI workloads, offering serverless indexes, hybrid search, and low-latency queries at scale.
Feature comparison
| Feature | pgvector | Pinecone |
|---|---|---|
| Pricing model | Free | Freemium |
| Starting price | Free (just Postgres) | $50/mo |
| Free tier | Yes | Yes |
| Open source | Yes | No |
| Type | Postgres extension | Managed |
| Free Tier | Unlimited | 2GB storage |
| Serverless | No | Yes |
| Self-hosted | Yes | No |
| Multi-tenant | Yes | Yes |
| Hybrid Search | Yes | Yes |
| Max Dimensions | 16000 | 20000 |
| Metadata Filtering | Yes | Yes |
pgvector
Vector similarity search for Postgres
Pros
- Use your existing Postgres
- No new infrastructure
- Transactional guarantees with vectors
- Free — pay only for Postgres
Cons
- Slower than purpose-built vector DBs at scale
- Index build times grow with data
- Not ideal for 100M+ vectors
Pinecone
The vector database for AI applications
Pros
- Purpose-built for production RAG
- Serverless pricing scales down to zero
- Best-in-class latency at scale
- Simple SDK in every language
Cons
- Closed source
- Costs scale with pod hours
- Fewer features than general-purpose DBs
Which should you choose?
Choose pgvector if you value open source and want the option to self-host, and a free tier is important for your stage. Choose Pinecone if a free tier is important for your stage.